Unmanned Aerial Vehicles (UAVs) have become an increasingly common tool for performing a variety of flight missions and tasks. Indeed, in recent years, the reduced cost of using UAVs, especially compared to the cost of chartering manned aerial vehicles, has given many businesses and individuals the opportunity to engage in a variety of previously cost-prohibitive activities. For example, it is now common for individuals and businesses to utilize UAVs to perform flight missions for capturing digital aerial images in a variety of contexts, such as construction, mining, surveying, or land conservation.
Many UAV missions or tasks require very accurate knowledge of the position of the UAV. For example, some conventional systems generate three-dimensional models of a site utilizing digital aerial images of the site captured by a camera affixed to a UAV in flight. The positions of the camera affixed to the UAV at the various times that the camera captures the digital aerial images can be significant to the accuracy of the resulting three-dimensional model.
Some conventional survey location systems identify UAV positions by utilizing survey ground control points. In particular, these conventional survey location systems set up accurate ground control points on the Earth that a UAV captures in digital aerial images. UAVs can then utilize the digital aerial images portraying the ground control points to determine the position of the UAV (as well as a camera affixed to the UAV). Although these conventional survey location systems can identify UAV position with some accuracy, these conventional systems also have a variety of problems. For instance, it is often expensive and highly time-consuming to place and identify ground control points on a given site. In addition, survey ground control points require maintenance for continued visibility and uniformity over time. Moreover, the placement of survey ground control points introduces the possibility of human error.
Other conventional GPS location systems seek to avoid these problems by determining the precise position of a UAV using GPS technology that analyzes the contents of a carrier signal from a satellite to identify the location of an antennae affixed to the UAV. However, traditional GPS systems also have a number of problems. For example, atmospheric interference can cause inaccuracies in communications between satellites and signal receivers below the atmosphere, which often leads to imprecise GPS measurements (e.g., an error tolerance of decimeters).
Some conventional systems attempt to correct these inaccuracies by utilizing real time kinematic (RTK) networks. Specifically, conventional RTK location systems can utilize RTK networks that include reference stations with known positions in the vicinity of the UAV to correct for atmospheric (or other) inaccuracies. Although these conventional location systems can utilize RTK networks to identify the position of a UAV, they also have their own problems. For example, RTK reference stations are typically expensive (e.g., $10,000-$20,000 to purchase hardware), hard to use (e.g., difficult to operate correctly without special training), and introduce a large amount of human error (e.g., if measurements of base antenna is off in setting up an RTK station, output data will be compromised). Some conventional location systems avoid these costs by purchasing data from an established RTK network. However, purchasing RTK data to determine the position for a UAV is also typically quite expensive (e.g., $2,000-$3,000 annually) and only partially effective (e.g., coverage differs based on network provider and does not cover the entire globe).
Accordingly, a number of problems and disadvantages exist with conventional systems for precisely, accurately, and inexpensively determining the position of a UAV.